Overview

Dataset statistics

Number of variables18
Number of observations1000
Missing cells638
Missing cells (%)3.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory140.8 KiB
Average record size in memory144.1 B

Variable types

CAT11
NUM7

Reproduction

Analysis started2020-07-18 05:01:03.680504
Analysis finished2020-07-18 05:02:18.093883
Duration1 minute and 14.41 seconds
Versionpandas-profiling v2.8.0
Command linepandas_profiling --config_file config.yaml [YOUR_FILE.csv]
Download configurationconfig.yaml

Warnings

Title has a high cardinality: 999 distinct values High cardinality
Director has a high cardinality: 644 distinct values High cardinality
Actors has a high cardinality: 996 distinct values High cardinality
Actor-1 has a high cardinality: 525 distinct values High cardinality
Actor-2 has a high cardinality: 692 distinct values High cardinality
Actor-3 has a high cardinality: 788 distinct values High cardinality
Actor-4 has a high cardinality: 897 distinct values High cardinality
Revenue (Millions) has 128 (12.8%) missing values Missing
Metascore has 64 (6.4%) missing values Missing
Genre-2 has 105 (10.5%) missing values Missing
Genre-3 has 340 (34.0%) missing values Missing
Title is uniformly distributed Uniform
Director is uniformly distributed Uniform
Actors is uniformly distributed Uniform
Actor-2 is uniformly distributed Uniform
Actor-3 is uniformly distributed Uniform
Actor-4 is uniformly distributed Uniform
Rank has unique values Unique
Description has unique values Unique

Variables

Rank
Real number (ℝ≥0)

UNIQUE

Distinct count1000
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean500.5
Minimum1
Maximum1000
Zeros0
Zeros (%)0.0%
Memory size7.8 KiB
2020-07-18T05:02:18.639122image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile50.95
Q1250.75
median500.5
Q3750.25
95-th percentile950.05
Maximum1000
Range999
Interquartile range (IQR)499.5

Descriptive statistics

Standard deviation288.8194361
Coefficient of variation (CV)0.5770618104
Kurtosis-1.2
Mean500.5
Median Absolute Deviation (MAD)250
Skewness0
Sum500500
Variance83416.66667
2020-07-18T05:02:19.323120image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
100010.1%
 
32910.1%
 
34210.1%
 
34110.1%
 
34010.1%
 
33910.1%
 
33810.1%
 
33710.1%
 
33610.1%
 
33510.1%
 
Other values (990)99099.0%
 
ValueCountFrequency (%) 
110.1%
 
210.1%
 
310.1%
 
410.1%
 
510.1%
 
ValueCountFrequency (%) 
100010.1%
 
99910.1%
 
99810.1%
 
99710.1%
 
99610.1%
 

Title
Categorical

HIGH CARDINALITY
UNIFORM

Distinct count999
Unique (%)99.9%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
The Host
 
2
Easy A
 
1
The Maze Runner
 
1
Neighbors 2: Sorority Rising
 
1
Alexander and the Terrible, Horrible, No Good, Very Bad Day
 
1
Other values (994)
994
ValueCountFrequency (%) 
The Host20.2%
 
Easy A10.1%
 
The Maze Runner10.1%
 
Neighbors 2: Sorority Rising10.1%
 
Alexander and the Terrible, Horrible, No Good, Very Bad Day10.1%
 
Project X10.1%
 
The Thinning10.1%
 
Pain & Gain10.1%
 
Dark Places10.1%
 
Scott Pilgrim vs. the World10.1%
 
Other values (989)98998.9%
 
2020-07-18T05:02:20.315199image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Length

Max length61
Median length13
Mean length14.539
Min length2

Description
Categorical

UNIQUE

Distinct count1000
Unique (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
A New York writer on sex and love is finally getting married to her Mr. Big. But her three best girlfriends must console her after one of them inadvertently leads Mr. Big to jilt her.
 
1
A dying CIA agent trying to reconnect with his estranged daughter is offered an experimental drug that could save his life in exchange for one last assignment.
 
1
When their new next-door neighbors turn out to be a sorority even more debaucherous than the fraternity previously living there, Mac and Kelly team with their former enemy, Teddy, to bring the girls down.
 
1
Disgruntled Korean War veteran Walt Kowalski sets out to reform his neighbor, a Hmong teenager who tried to steal Kowalski's prized possession: a 1972 Gran Torino.
 
1
Three years after Mike bowed out of the stripper life at the top of his game, he and the remaining Kings of Tampa hit the road to Myrtle Beach to put on one last blow-out performance.
 
1
Other values (995)
995
ValueCountFrequency (%) 
A New York writer on sex and love is finally getting married to her Mr. Big. But her three best girlfriends must console her after one of them inadvertently leads Mr. Big to jilt her.10.1%
 
A dying CIA agent trying to reconnect with his estranged daughter is offered an experimental drug that could save his life in exchange for one last assignment.10.1%
 
When their new next-door neighbors turn out to be a sorority even more debaucherous than the fraternity previously living there, Mac and Kelly team with their former enemy, Teddy, to bring the girls down.10.1%
 
Disgruntled Korean War veteran Walt Kowalski sets out to reform his neighbor, a Hmong teenager who tried to steal Kowalski's prized possession: a 1972 Gran Torino.10.1%
 
Three years after Mike bowed out of the stripper life at the top of his game, he and the remaining Kings of Tampa hit the road to Myrtle Beach to put on one last blow-out performance.10.1%
 
In the aftermath of a family tragedy, an aspiring author is torn between love for her childhood friend and the temptation of a mysterious outsider. Trying to escape the ghosts of her past, she is swept away to a house that breathes, bleeds - and remembers.10.1%
 
For three Border Patrol agents working a remote desert checkpoint, the contents of one car will reveal an insidious plot within their own ranks. The next 24 hours will take them on a treacherous journey that could cost them their lives.10.1%
 
Two sisters decide to throw one last house party before their parents sell their family home.10.1%
 
Manolo, a young man who is torn between fulfilling the expectations of his family and following his heart, embarks on an adventure that spans three fantastic worlds where he must face his greatest fears.10.1%
 
An elite military unit comprised of special operatives known as G.I. Joe, operating out of The Pit, takes on an evil organization led by a notorious arms dealer.10.1%
 
Other values (990)99099.0%
 
2020-07-18T05:02:21.299654image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Length

Max length421
Median length159
Mean length163.232
Min length42

Director
Categorical

HIGH CARDINALITY
UNIFORM

Distinct count644
Unique (%)64.4%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
Ridley Scott
 
8
M. Night Shyamalan
 
6
Paul W.S. Anderson
 
6
David Yates
 
6
Michael Bay
 
6
Other values (639)
968
ValueCountFrequency (%) 
Ridley Scott80.8%
 
M. Night Shyamalan60.6%
 
Paul W.S. Anderson60.6%
 
David Yates60.6%
 
Michael Bay60.6%
 
Christopher Nolan50.5%
 
Denis Villeneuve50.5%
 
Martin Scorsese50.5%
 
Antoine Fuqua50.5%
 
Woody Allen50.5%
 
Other values (634)94394.3%
 
2020-07-18T05:02:22.338564image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Length

Max length32
Median length13
Mean length13.139
Min length3

Actors
Categorical

HIGH CARDINALITY
UNIFORM

Distinct count996
Unique (%)99.6%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
Daniel Radcliffe, Emma Watson, Rupert Grint, Michael Gambon
 
2
Gerard Butler, Aaron Eckhart, Morgan Freeman,Angela Bassett
 
2
Shia LaBeouf, Megan Fox, Josh Duhamel, Tyrese Gibson
 
2
Jennifer Lawrence, Josh Hutcherson, Liam Hemsworth, Woody Harrelson
 
2
Samuel L. Jackson, Julianna Margulies, Nathan Phillips, Rachel Blanchard
 
1
Other values (991)
991
ValueCountFrequency (%) 
Daniel Radcliffe, Emma Watson, Rupert Grint, Michael Gambon20.2%
 
Gerard Butler, Aaron Eckhart, Morgan Freeman,Angela Bassett20.2%
 
Shia LaBeouf, Megan Fox, Josh Duhamel, Tyrese Gibson20.2%
 
Jennifer Lawrence, Josh Hutcherson, Liam Hemsworth, Woody Harrelson20.2%
 
Samuel L. Jackson, Julianna Margulies, Nathan Phillips, Rachel Blanchard10.1%
 
Kurt Russell, Zoë Bell, Rosario Dawson, Vanessa Ferlito10.1%
 
Owen Wilson, Rachel McAdams, Kathy Bates, Kurt Fuller10.1%
 
Casey Affleck, Chiwetel Ejiofor, Anthony Mackie,Aaron Paul10.1%
 
Emma Roberts, Dave Franco, Emily Meade, Miles Heizer10.1%
 
Kristen Stewart, Robert Pattinson, Billy Burke,Sarah Clarke10.1%
 
Other values (986)98698.6%
 
2020-07-18T05:02:23.294615image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Length

Max length77
Median length58
Mean length58.288
Min length43

Year
Real number (ℝ≥0)

Distinct count11
Unique (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2012.783
Minimum2006
Maximum2016
Zeros0
Zeros (%)0.0%
Memory size7.8 KiB
2020-07-18T05:02:24.812530image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum2006
5-th percentile2007
Q12010
median2014
Q32016
95-th percentile2016
Maximum2016
Range10
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.205961508
Coefficient of variation (CV)0.00159280037
Kurtosis-0.8219639755
Mean2012.783
Median Absolute Deviation (MAD)2
Skewness-0.6898787091
Sum2012783
Variance10.27818919
2020-07-18T05:02:25.551524image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
201629729.7%
 
201512712.7%
 
2014989.8%
 
2013919.1%
 
2012646.4%
 
2011636.3%
 
2010606.0%
 
2007535.3%
 
2008525.2%
 
2009515.1%
 
ValueCountFrequency (%) 
2006444.4%
 
2007535.3%
 
2008525.2%
 
2009515.1%
 
2010606.0%
 
ValueCountFrequency (%) 
201629729.7%
 
201512712.7%
 
2014989.8%
 
2013919.1%
 
2012646.4%
 

Runtime (Minutes)
Real number (ℝ≥0)

Distinct count94
Unique (%)9.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean113.172
Minimum66
Maximum191
Zeros0
Zeros (%)0.0%
Memory size7.8 KiB
2020-07-18T05:02:26.395365image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum66
5-th percentile88
Q1100
median111
Q3123
95-th percentile150
Maximum191
Range125
Interquartile range (IQR)23

Descriptive statistics

Standard deviation18.81090817
Coefficient of variation (CV)0.1662152138
Kurtosis0.8583211032
Mean113.172
Median Absolute Deviation (MAD)12
Skewness0.8467127314
Sum113172
Variance353.8502663
2020-07-18T05:02:27.060484image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
108313.1%
 
100282.8%
 
117272.7%
 
110262.6%
 
106262.6%
 
118262.6%
 
102252.5%
 
112242.4%
 
104232.3%
 
123232.3%
 
Other values (84)74174.1%
 
ValueCountFrequency (%) 
6610.1%
 
7320.2%
 
8020.2%
 
8150.5%
 
8210.1%
 
ValueCountFrequency (%) 
19110.1%
 
18710.1%
 
18030.3%
 
17210.1%
 
17010.1%
 

Rating
Real number (ℝ≥0)

Distinct count55
Unique (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.723199999999999
Minimum1.9
Maximum9.0
Zeros0
Zeros (%)0.0%
Memory size7.8 KiB
2020-07-18T05:02:27.813784image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum1.9
5-th percentile5.1
Q16.2
median6.8
Q37.4
95-th percentile8.1
Maximum9
Range7.1
Interquartile range (IQR)1.2

Descriptive statistics

Standard deviation0.9454287893
Coefficient of variation (CV)0.1406218451
Kurtosis1.322270288
Mean6.7232
Median Absolute Deviation (MAD)0.6
Skewness-0.7431419408
Sum6723.2
Variance0.8938355956
2020-07-18T05:02:28.676540image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
7.1525.2%
 
6.7484.8%
 
7464.6%
 
6.3444.4%
 
6.6424.2%
 
7.2424.2%
 
7.3424.2%
 
6.5404.0%
 
7.8404.0%
 
6.2373.7%
 
Other values (45)56756.7%
 
ValueCountFrequency (%) 
1.910.1%
 
2.720.2%
 
3.210.1%
 
3.520.2%
 
3.720.2%
 
ValueCountFrequency (%) 
910.1%
 
8.820.2%
 
8.630.3%
 
8.560.6%
 
8.440.4%
 

Votes
Real number (ℝ≥0)

Distinct count997
Unique (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean169808.255
Minimum61
Maximum1791916
Zeros0
Zeros (%)0.0%
Memory size7.8 KiB
2020-07-18T05:02:29.503489image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum61
5-th percentile1260.35
Q136309
median110799
Q3239909.75
95-th percentile526551.85
Maximum1791916
Range1791855
Interquartile range (IQR)203600.75

Descriptive statistics

Standard deviation188762.6475
Coefficient of variation (CV)1.111622327
Kurtosis11.3126809
Mean169808.255
Median Absolute Deviation (MAD)88402
Skewness2.507918483
Sum169808255
Variance3.56313371e+10
2020-07-18T05:02:30.330441image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
142720.2%
 
9714120.2%
 
29120.2%
 
53111210.1%
 
70210.1%
 
4780410.1%
 
22661910.1%
 
7646910.1%
 
12569310.1%
 
17455310.1%
 
Other values (987)98798.7%
 
ValueCountFrequency (%) 
6110.1%
 
9610.1%
 
10210.1%
 
11510.1%
 
16410.1%
 
ValueCountFrequency (%) 
179191610.1%
 
158362510.1%
 
122264510.1%
 
104774710.1%
 
104558810.1%
 

Revenue (Millions)
Real number (ℝ≥0)

MISSING

Distinct count814
Unique (%)93.3%
Missing128
Missing (%)12.8%
Infinite0
Infinite (%)0.0%
Mean82.95637614678898
Minimum0.0
Maximum936.63
Zeros1
Zeros (%)0.1%
Memory size7.8 KiB
2020-07-18T05:02:31.217016image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.211
Q113.27
median47.985
Q3113.715
95-th percentile293.88
Maximum936.63
Range936.63
Interquartile range (IQR)100.445

Descriptive statistics

Standard deviation103.2535405
Coefficient of variation (CV)1.244672746
Kurtosis10.60763453
Mean82.95637615
Median Absolute Deviation (MAD)41.285
Skewness2.592515866
Sum72337.96
Variance10661.29362
2020-07-18T05:02:31.881879image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
0.0370.7%
 
0.0150.5%
 
0.0440.4%
 
0.0240.4%
 
0.3240.4%
 
0.0540.4%
 
1.2930.3%
 
0.1530.3%
 
2.230.3%
 
0.5430.3%
 
Other values (804)83283.2%
 
(Missing)12812.8%
 
ValueCountFrequency (%) 
010.1%
 
0.0150.5%
 
0.0240.4%
 
0.0370.7%
 
0.0440.4%
 
ValueCountFrequency (%) 
936.6310.1%
 
760.5110.1%
 
652.1810.1%
 
623.2810.1%
 
533.3210.1%
 

Metascore
Real number (ℝ≥0)

MISSING

Distinct count84
Unique (%)9.0%
Missing64
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean58.98504273504273
Minimum11.0
Maximum100.0
Zeros0
Zeros (%)0.0%
Memory size7.8 KiB
2020-07-18T05:02:32.621192image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile31
Q147
median59.5
Q372
95-th percentile85
Maximum100
Range89
Interquartile range (IQR)25

Descriptive statistics

Standard deviation17.19475702
Coefficient of variation (CV)0.2915104614
Kurtosis-0.6122051468
Mean58.98504274
Median Absolute Deviation (MAD)12.5
Skewness-0.1238873467
Sum55210
Variance295.6596691
2020-07-18T05:02:33.269366image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
66252.5%
 
72252.5%
 
68252.5%
 
64242.4%
 
57232.3%
 
51222.2%
 
65222.2%
 
48212.1%
 
81212.1%
 
76212.1%
 
Other values (74)70770.7%
 
(Missing)646.4%
 
ValueCountFrequency (%) 
1110.1%
 
1510.1%
 
1610.1%
 
1840.4%
 
1910.1%
 
ValueCountFrequency (%) 
10010.1%
 
9910.1%
 
9810.1%
 
9640.4%
 
9530.3%
 

Actor-1
Categorical

HIGH CARDINALITY

Distinct count525
Unique (%)52.5%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
Mark Wahlberg
 
11
Christian Bale
 
11
Jake Gyllenhaal
 
9
Denzel Washington
 
9
Leonardo DiCaprio
 
9
Other values (520)
951
ValueCountFrequency (%) 
Mark Wahlberg111.1%
 
Christian Bale111.1%
 
Jake Gyllenhaal90.9%
 
Denzel Washington90.9%
 
Leonardo DiCaprio90.9%
 
Brad Pitt90.9%
 
Adam Sandler90.9%
 
Will Smith90.9%
 
Tom Hanks80.8%
 
Daniel Radcliffe80.8%
 
Other values (515)90890.8%
 
2020-07-18T05:02:34.144537image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Length

Max length23
Median length13
Mean length13.132
Min length7

Actor-2
Categorical

HIGH CARDINALITY
UNIFORM

Distinct count692
Unique (%)69.2%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
Cate Blanchett
 
8
Michelle Monaghan
 
6
Rose Byrne
 
6
Jonah Hill
 
5
Robert Pattinson
 
5
Other values (687)
970
ValueCountFrequency (%) 
Cate Blanchett80.8%
 
Michelle Monaghan60.6%
 
Rose Byrne60.6%
 
Jonah Hill50.5%
 
Robert Pattinson50.5%
 
Kristen Wiig50.5%
 
Emma Watson50.5%
 
Hugh Jackman50.5%
 
Anne Hathaway50.5%
 
Aaron Eckhart40.4%
 
Other values (682)94694.6%
 
2020-07-18T05:02:35.112703image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Length

Max length27
Median length14
Mean length14.125
Min length6

Actor-3
Categorical

HIGH CARDINALITY
UNIFORM

Distinct count788
Unique (%)78.8%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
Morgan Freeman
 
6
Liam Hemsworth
 
5
Mark Ruffalo
 
4
Scarlett Johansson
 
4
Chiwetel Ejiofor
 
4
Other values (783)
977
ValueCountFrequency (%) 
Morgan Freeman60.6%
 
Liam Hemsworth50.5%
 
Mark Ruffalo40.4%
 
Scarlett Johansson40.4%
 
Chiwetel Ejiofor40.4%
 
Rupert Grint40.4%
 
Samuel L. Jackson40.4%
 
Anna Kendrick40.4%
 
Willem Dafoe40.4%
 
Owen Wilson40.4%
 
Other values (778)95795.7%
 
2020-07-18T05:02:36.063423image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Length

Max length26
Median length14
Mean length14.15
Min length7

Actor-4
Categorical

HIGH CARDINALITY
UNIFORM

Distinct count897
Unique (%)89.8%
Missing1
Missing (%)0.1%
Memory size7.8 KiB
Woody Harrelson
 
5
Ralph Fiennes
 
4
Mark Strong
 
3
Emily Blunt
 
3
Ben Kingsley
 
3
Other values (892)
981
ValueCountFrequency (%) 
Woody Harrelson50.5%
 
Ralph Fiennes40.4%
 
Mark Strong30.3%
 
Emily Blunt30.3%
 
Ben Kingsley30.3%
 
Judi Dench30.3%
 
Chloë Grace Moretz30.3%
 
Michael Caine30.3%
 
Philip Seymour Hoffman30.3%
 
Stellan Skarsgård30.3%
 
Other values (887)96696.6%
 
2020-07-18T05:02:37.092520image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Length

Max length27
Median length13
Mean length13.885
Min length3

Genre-1
Categorical

Distinct count13
Unique (%)1.3%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
Action
293
Drama
195
Comedy
175
Adventure
75
Crime
71
Other values (8)
191
ValueCountFrequency (%) 
Action29329.3%
 
Drama19519.5%
 
Comedy17517.5%
 
Adventure757.5%
 
Crime717.1%
 
Biography646.4%
 
Animation494.9%
 
Horror464.6%
 
Mystery131.3%
 
Thriller101.0%
 
Other values (3)90.9%
 
2020-07-18T05:02:38.143206image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Length

Max length9
Median length6
Mean length6.337
Min length5

Genre-2
Categorical

MISSING

Distinct count19
Unique (%)2.1%
Missing105
Missing (%)10.5%
Memory size7.8 KiB
Drama
238
Adventure
175
Romance
69
Comedy
62
Crime
 
58
Other values (14)
293
ValueCountFrequency (%) 
Drama23823.8%
 
Adventure17517.5%
 
Romance696.9%
 
Comedy626.2%
 
Crime585.8%
 
Thriller525.2%
 
Mystery494.9%
 
Horror494.9%
 
Fantasy353.5%
 
Sci-Fi282.8%
 
Other values (9)808.0%
 
(Missing)10510.5%
 
2020-07-18T05:02:39.187927image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Length

Max length9
Median length6
Mean length6.202
Min length3

Genre-3
Categorical

MISSING

Distinct count18
Unique (%)2.7%
Missing340
Missing (%)34.0%
Memory size7.8 KiB
Thriller
133
Sci-Fi
89
Drama
80
Romance
70
Fantasy
62
Other values (13)
226
ValueCountFrequency (%) 
Thriller13313.3%
 
Sci-Fi898.9%
 
Drama808.0%
 
Romance707.0%
 
Fantasy626.2%
 
Mystery444.4%
 
Comedy424.2%
 
Horror242.4%
 
Family242.4%
 
History212.1%
 
Other values (8)717.1%
 
(Missing)34034.0%
 
2020-07-18T05:02:40.213891image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Length

Max length9
Median length6
Mean length5.336
Min length3

Interactions

2020-07-18T05:01:20.139277image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
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2020-07-18T05:01:23.058836image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-18T05:01:23.986159image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-18T05:01:24.921818image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-18T05:01:25.800230image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-18T05:01:26.772606image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
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2020-07-18T05:01:28.845059image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
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2020-07-18T05:01:33.999470image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
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2020-07-18T05:01:59.075504image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-18T05:01:59.985888image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-18T05:02:01.057814image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-18T05:02:02.049493image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-18T05:02:02.975020image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-18T05:02:03.909845image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-18T05:02:04.916397image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-18T05:02:06.109279image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-18T05:02:07.122168image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-18T05:02:08.102316image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-18T05:02:09.006615image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Correlations

2020-07-18T05:02:41.074941image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-07-18T05:02:42.303630image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-07-18T05:02:43.510705image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-07-18T05:02:44.767531image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2020-07-18T05:02:46.087694image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2020-07-18T05:02:11.039509image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-18T05:02:14.154714image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-18T05:02:15.895243image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-18T05:02:16.992980image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Sample

First rows

RankTitleDescriptionDirectorActorsYearRuntime (Minutes)RatingVotesRevenue (Millions)MetascoreActor-1Actor-2Actor-3Actor-4Genre-1Genre-2Genre-3
01Guardians of the GalaxyA group of intergalactic criminals are forced to work together to stop a fanatical warrior from taking control of the universe.James GunnChris Pratt, Vin Diesel, Bradley Cooper, Zoe Saldana20141218.1757074333.1376.0Chris PrattVin DieselBradley CooperZoe SaldanaActionAdventureSci-Fi
12PrometheusFollowing clues to the origin of mankind, a team finds a structure on a distant moon, but they soon realize they are not alone.Ridley ScottNoomi Rapace, Logan Marshall-Green, Michael Fassbender, Charlize Theron20121247.0485820126.4665.0Noomi RapaceLogan Marshall-GreenMichael FassbenderCharlize TheronAdventureMysterySci-Fi
23SplitThree girls are kidnapped by a man with a diagnosed 23 distinct personalities. They must try to escape before the apparent emergence of a frightful new 24th.M. Night ShyamalanJames McAvoy, Anya Taylor-Joy, Haley Lu Richardson, Jessica Sula20161177.3157606138.1262.0James McAvoyAnya Taylor-JoyHaley Lu RichardsonJessica SulaHorrorThrillerNaN
34SingIn a city of humanoid animals, a hustling theater impresario's attempt to save his theater with a singing competition becomes grander than he anticipates even as its finalists' find that their lives will never be the same.Christophe LourdeletMatthew McConaughey,Reese Witherspoon, Seth MacFarlane, Scarlett Johansson20161087.260545270.3259.0Matthew McConaugheyReese WitherspoonSeth MacFarlaneScarlett JohanssonAnimationComedyFamily
45Suicide SquadA secret government agency recruits some of the most dangerous incarcerated super-villains to form a defensive task force. Their first mission: save the world from the apocalypse.David AyerWill Smith, Jared Leto, Margot Robbie, Viola Davis20161236.2393727325.0240.0Will SmithJared LetoMargot RobbieViola DavisActionAdventureFantasy
56The Great WallEuropean mercenaries searching for black powder become embroiled in the defense of the Great Wall of China against a horde of monstrous creatures.Yimou ZhangMatt Damon, Tian Jing, Willem Dafoe, Andy Lau20161036.15603645.1342.0Matt DamonTian JingWillem DafoeAndy LauActionAdventureFantasy
67La La LandA jazz pianist falls for an aspiring actress in Los Angeles.Damien ChazelleRyan Gosling, Emma Stone, Rosemarie DeWitt, J.K. Simmons20161288.3258682151.0693.0Ryan GoslingEmma StoneRosemarie DeWittJ.K. SimmonsComedyDramaMusic
78MindhornA has-been actor best known for playing the title character in the 1980s detective series "Mindhorn" must work with the police when a serial killer says that he will only speak with Detective Mindhorn, whom he believes to be a real person.Sean FoleyEssie Davis, Andrea Riseborough, Julian Barratt,Kenneth Branagh2016896.42490NaN71.0Essie DavisAndrea RiseboroughJulian BarrattKenneth BranaghComedyNaNNaN
89The Lost City of ZA true-life drama, centering on British explorer Col. Percival Fawcett, who disappeared while searching for a mysterious city in the Amazon in the 1920s.James GrayCharlie Hunnam, Robert Pattinson, Sienna Miller, Tom Holland20161417.171888.0178.0Charlie HunnamRobert PattinsonSienna MillerTom HollandActionAdventureBiography
910PassengersA spacecraft traveling to a distant colony planet and transporting thousands of people has a malfunction in its sleep chambers. As a result, two passengers are awakened 90 years early.Morten TyldumJennifer Lawrence, Chris Pratt, Michael Sheen,Laurence Fishburne20161167.0192177100.0141.0Jennifer LawrenceChris PrattMichael SheenLaurence FishburneAdventureDramaRomance

Last rows

RankTitleDescriptionDirectorActorsYearRuntime (Minutes)RatingVotesRevenue (Millions)MetascoreActor-1Actor-2Actor-3Actor-4Genre-1Genre-2Genre-3
990991Underworld: Rise of the LycansAn origins story centered on the centuries-old feud between the race of aristocratic vampires and their onetime slaves, the Lycans.Patrick TatopoulosRhona Mitra, Michael Sheen, Bill Nighy, Steven Mackintosh2009926.612970845.8044.0Rhona MitraMichael SheenBill NighySteven MackintoshActionAdventureFantasy
991992Taare Zameen ParAn eight-year-old boy is thought to be a lazy trouble-maker, until the new art teacher has the patience and compassion to discover the real problem behind his struggles in school.Aamir KhanDarsheel Safary, Aamir Khan, Tanay Chheda, Sachet Engineer20071658.51026971.2042.0Darsheel SafaryAamir KhanTanay ChhedaSachet EngineerDramaFamilyMusic
992993Take Me Home TonightFour years after graduation, an awkward high school genius uses his sister's boyfriend's Labor Day party as the perfect opportunity to make his move on his high school crush.Michael DowseTopher Grace, Anna Faris, Dan Fogler, Teresa Palmer2011976.3454196.92NaNTopher GraceAnna FarisDan FoglerTeresa PalmerComedyDramaRomance
993994Resident Evil: AfterlifeWhile still out to destroy the evil Umbrella Corporation, Alice joins a group of survivors living in a prison surrounded by the infected who also want to relocate to the mysterious but supposedly unharmed safe haven known only as Arcadia.Paul W.S. AndersonMilla Jovovich, Ali Larter, Wentworth Miller,Kim Coates2010975.914090060.1337.0Milla JovovichAli LarterWentworth MillerKim CoatesActionAdventureHorror
994995Project X3 high school seniors throw a birthday party to make a name for themselves. As the night progresses, things spiral out of control as word of the party spreads.Nima NourizadehThomas Mann, Oliver Cooper, Jonathan Daniel Brown, Dax Flame2012886.716408854.7248.0Thomas MannOliver CooperJonathan Daniel BrownDax FlameComedyNaNNaN
995996Secret in Their EyesA tight-knit team of rising investigators, along with their supervisor, is suddenly torn apart when they discover that one of their own teenage daughters has been brutally murdered.Billy RayChiwetel Ejiofor, Nicole Kidman, Julia Roberts, Dean Norris20151116.227585NaN45.0Chiwetel EjioforNicole KidmanJulia RobertsDean NorrisCrimeDramaMystery
996997Hostel: Part IIThree American college students studying abroad are lured to a Slovakian hostel, and discover the grim reality behind it.Eli RothLauren German, Heather Matarazzo, Bijou Phillips, Roger Bart2007945.57315217.5446.0Lauren GermanHeather MatarazzoBijou PhillipsRoger BartHorrorNaNNaN
997998Step Up 2: The StreetsRomantic sparks occur between two dance students from different backgrounds at the Maryland School of the Arts.Jon M. ChuRobert Hoffman, Briana Evigan, Cassie Ventura, Adam G. Sevani2008986.27069958.0150.0Robert HoffmanBriana EviganCassie VenturaAdam G. SevaniDramaMusicRomance
998999Search PartyA pair of friends embark on a mission to reunite their pal with the woman he was going to marry.Scot ArmstrongAdam Pally, T.J. Miller, Thomas Middleditch,Shannon Woodward2014935.64881NaN22.0Adam PallyT.J. MillerThomas MiddleditchShannon WoodwardAdventureComedyNaN
9991000Nine LivesA stuffy businessman finds himself trapped inside the body of his family's cat.Barry SonnenfeldKevin Spacey, Jennifer Garner, Robbie Amell,Cheryl Hines2016875.31243519.6411.0Kevin SpaceyJennifer GarnerRobbie AmellCheryl HinesComedyFamilyFantasy